SMILE

Stochastic Models for the Inference of Life Evolution

Multidimensional (co)evolutionary stability

Débarre, F., Nuismer, S. L., Doebeli, M.

The American Naturalist

2014

The complexity of biotic and abiotic environmental conditions is such that the fitness of individuals is likely to depend on multiple traits. Using a synthetic framework of phenotypic evolution that draws from adaptive dynamics and quantitative genetics approaches, we explore how the number of traits under selection influences convergence stability and evolutionary stability in models for coevolution in multidimensional phenotype spaces. Our results allow us to identify three different effects of trait dimensionality on stability. First are (i) a "combinatorial effect": without epistasis and genetic correlations, a higher number of trait dimensions offers more opportunities for equilibria to be unstable; and (ii) epistatic interactions, that is, fitness interactions between traits, which tend to destabilize evolutionary equilibria; this effect increases with the dimension of phenotype space. These first two effects influence both convergence stability and evolutionary stability, while (iii) genetic correlations (due, e.g., to pleiotropy or linkage disequilibrium) can affect only convergence stability. We illustrate the general prediction that increased dimensionality destabilizes evolutionary equilibria using examples drawn from well-studied classical models of frequency-dependent competition for resources, adaptation to a spatially heterogeneous environment, and antagonistic coevolution. In addition, our analyses show that increased dimensionality can favor diversification, for example, in the form of local adaptation, as well as evolutionary escape.

Bibtex

@article{debarre_multidimensional_2014,
Author = {Débarre, F. and Nuismer, S. L. and Doebeli, M.},
Title = {Multidimensional (co)evolutionary stability},
Journal = {The American Naturalist},
Volume = {184},
Number = {2},
Pages = {158--171},
abstract = {The complexity of biotic and abiotic environmental
conditions is such that the fitness of individuals is
likely to depend on multiple traits. Using a synthetic
framework of phenotypic evolution that draws from
adaptive dynamics and quantitative genetics approaches,
we explore how the number of traits under selection
influences convergence stability and evolutionary
stability in models for coevolution in multidimensional
phenotype spaces. Our results allow us to identify
three different effects of trait dimensionality on
stability. First are (i) a "combinatorial effect":
without epistasis and genetic correlations, a higher
number of trait dimensions offers more opportunities
for equilibria to be unstable; and (ii) epistatic
interactions, that is, fitness interactions between
traits, which tend to destabilize evolutionary
equilibria; this effect increases with the dimension of
phenotype space. These first two effects influence both
convergence stability and evolutionary stability, while
(iii) genetic correlations (due, e.g., to pleiotropy or
linkage disequilibrium) can affect only convergence
stability. We illustrate the general prediction that
increased dimensionality destabilizes evolutionary
equilibria using examples drawn from well-studied
classical models of frequency-dependent competition for
resources, adaptation to a spatially heterogeneous
environment, and antagonistic coevolution. In addition,
our analyses show that increased dimensionality can
favor diversification, for example, in the form of
local adaptation, as well as evolutionary escape.},
doi = {10.1086/677137},
issn = {1537-5323},
language = {eng},
month = aug,
pmid = {25058277},
year = 2014
}

Link to the article

Accéder à l'article grâce à son DOI.